3,397 research outputs found

    Cytoplasmic PML promotes TGF-β-associated epithelial–mesenchymal transition and invasion in prostate cancer

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    Epithelial–mesenchymal transition (EMT) is a key event that is involved in the invasion and dissemination of cancer cells. Although typically considered as having tumour-suppressive properties, transforming growth factor (TGF)-β signalling is altered during cancer and has been associated with the invasion of cancer cells and metastasis. In this study, we report a previously unknown role for the cytoplasmic promyelocytic leukaemia (cPML) tumour suppressor in TGF-β signalling-induced regulation of prostate cancer-associated EMT and invasion. We demonstrate that cPML promotes a mesenchymal phenotype and increases the invasiveness of prostate cancer cells. This event is associated with activation of TGF-β canonical signalling pathway through the induction of Sma and Mad related family 2 and 3 (SMAD2 and SMAD3) phosphorylation. Furthermore, the cytoplasmic localization of promyelocytic leukaemia (PML) is mediated by its nuclear export in a chromosomal maintenance 1 (CRM1)-dependent manner. This was clinically tested in prostate cancer tissue and shown that cytoplasmic PML and CRM1 co-expression correlates with reduced disease-specific survival. In summary, we provide evidence of dysfunctional TGF-β signalling occurring at an early stage in prostate cancer. We show that this disease pathway is mediated by cPML and CRM1 and results in a more aggressive cancer cell phenotype. We propose that the targeting of this pathway could be therapeutically exploited for clinical benefit

    What differences are detected by superiority trials or ruled out by noninferiority trials? A cross-sectional study on a random sample of two-hundred two-arms parallel group randomized clinical trials

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    <p>Abstract</p> <p>Background</p> <p>The smallest difference to be detected in superiority trials or the largest difference to be ruled out in noninferiority trials is a key determinant of sample size, but little guidance exists to help researchers in their choice. The objectives were to examine the distribution of differences that researchers aim to detect in clinical trials and to verify that those differences are smaller in noninferiority compared to superiority trials.</p> <p>Methods</p> <p>Cross-sectional study based on a random sample of two hundred two-arm, parallel group superiority (100) and noninferiority (100) randomized clinical trials published between 2004 and 2009 in 27 leading medical journals. The main outcome measure was the smallest difference in favor of the new treatment to be detected (superiority trials) or largest unfavorable difference to be ruled out (noninferiority trials) used for sample size computation, expressed as standardized difference in proportions, or standardized difference in means. Student t test and analysis of variance were used.</p> <p>Results</p> <p>The differences to be detected or ruled out varied considerably from one study to the next; e.g., for superiority trials, the standardized difference in means ranged from 0.007 to 0.87, and the standardized difference in proportions from 0.04 to 1.56. On average, superiority trials were designed to detect larger differences than noninferiority trials (standardized difference in proportions: mean 0.37 versus 0.27, <it>P </it>= 0.001; standardized difference in means: 0.56 versus 0.40, <it>P </it>= 0.006). Standardized differences were lower for mortality than for other outcomes, and lower in cardiovascular trials than in other research areas.</p> <p>Conclusions</p> <p>Superiority trials are designed to detect larger differences than noninferiority trials are designed to rule out. The variability between studies is considerable and is partly explained by the type of outcome and the medical context. A more explicit and rational approach to choosing the difference to be detected or to be ruled out in clinical trials may be desirable.</p

    What differences are detected by superiority trials or ruled out by noninferiority trials? A cross-sectional study on a random sample of two-hundred two-arms parallel group randomized clinical trials

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    BACKGROUND: The smallest difference to be detected in superiority trials or the largest difference to be ruled out in noninferiority trials is a key determinant of sample size, but little guidance exists to help researchers in their choice. The objectives were to examine the distribution of differences that researchers aim to detect in clinical trials and to verify that those differences are smaller in noninferiority compared to superiority trials. METHODS: Cross-sectional study based on a random sample of two hundred two-arm, parallel group superiority (100) and noninferiority (100) randomized clinical trials published between 2004 and 2009 in 27 leading medical journals. The main outcome measure was the smallest difference in favor of the new treatment to be detected (superiority trials) or largest unfavorable difference to be ruled out (noninferiority trials) used for sample size computation, expressed as standardized difference in proportions, or standardized difference in means. Student t test and analysis of variance were used. RESULTS: The differences to be detected or ruled out varied considerably from one study to the next; e.g., for superiority trials, the standardized difference in means ranged from 0.007 to 0.87, and the standardized difference in proportions from 0.04 to 1.56. On average, superiority trials were designed to detect larger differences than noninferiority trials (standardized difference in proportions: mean 0.37 versus 0.27, P = 0.001; standardized difference in means: 0.56 versus 0.40, P = 0.006). Standardized differences were lower for mortality than for other outcomes, and lower in cardiovascular trials than in other research areas. CONCLUSIONS: Superiority trials are designed to detect larger differences than noninferiority trials are designed to rule out. The variability between studies is considerable and is partly explained by the type of outcome and the medical context. A more explicit and rational approach to choosing the difference to be detected or to be ruled out in clinical trials may be desirable

    Does publication bias inflate the apparent efficacy of psychological treatment for major depressive disorder? A systematic review and meta-analysis of US national institutes of health-funded trials

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    Background The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression. Methods and Findings We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972–2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges’ g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the "true" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively. Conclusion The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression

    An Ecological Study of the Determinants of Differences in 2009 Pandemic Influenza Mortality Rates between Countries in Europe

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    Pandemic A (H1N1) 2009 mortality rates varied widely from one country to another. Our aim was to identify potential socioeconomic determinants of pandemic mortality and explain between-country variation.Based on data from a total of 30 European countries, we applied random-effects Poisson regression models to study the relationship between pandemic mortality rates (May 2009 to May 2010) and a set of representative environmental, health care-associated, economic and demographic country-level parameters. The study was completed by June 2010.Most regression approaches indicated a consistent, statistically significant inverse association between pandemic influenza-related mortality and per capita government expenditure on health. The findings were similar in univariable [coefficient: -0.00028, 95% Confidence Interval (CI): -0.00046, -0.00010, p = 0.002] and multivariable analyses (including all covariates, coefficient: -0.00107, 95% CI: -0.00196, -0.00018, p = 0.018). The estimate was barely insignificant when the multivariable model included only significant covariates from the univariate step (coefficient: -0.00046, 95% CI: -0.00095, 0.00003, p = 0.063).Our findings imply a significant inverse association between public spending on health and pandemic influenza mortality. In an attempt to interpret the estimated coefficient (-0.00028) for the per capita government expenditure on health, we observed that a rise of 100 international dollars was associated with a reduction in the pandemic influenza mortality rate by approximately 2.8%. However, further work needs to be done to unravel the mechanisms by which reduced government spending on health may have affected the 2009 pandemic influenza mortality

    Age-Related Attenuation of Dominant Hand Superiority

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    The decline of motor performance of the human hand-arm system with age is well-documented. While dominant hand performance is superior to that of the non-dominant hand in young individuals, little is known of possible age-related changes in hand dominance. We investigated age-related alterations of hand dominance in 20 to 90 year old subjects. All subjects were unambiguously right-handed according to the Edinburgh Handedness Inventory. In Experiment 1, motor performance for aiming, postural tremor, precision of arm-hand movement, speed of arm-hand movement, and wrist-finger speed tasks were tested. In Experiment 2, accelerometer-sensors were used to obtain objective records of hand use in everyday activities

    Determining the pneumococcal conjugate vaccine coverage required for indirect protection against vaccine-type pneumococcal carriage in low and middle-income countries: a protocol for a prospective observational study.

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    INTRODUCTION: Pneumococcal conjugate vaccines (PCVs) prevent disease through both direct protection of vaccinated individuals and indirect protection of unvaccinated individuals by reducing nasopharyngeal (NP) carriage and transmission of vaccine-type (VT) pneumococci. While the indirect effects of PCV vaccination are well described, the PCV coverage required to achieve the indirect effects is unknown. We will investigate the relationship between PCV coverage and VT carriage among undervaccinated children using hospital-based NP pneumococcal carriage surveillance at three sites in Asia and the Pacific. METHODS AND ANALYSIS: We are recruiting cases, defined as children aged 2-59 months admitted to participating hospitals with acute respiratory infection in Lao People's Democratic Republic, Mongolia and Papua New Guinea. Thirteen-valent PCV status is obtained from written records. NP swabs are collected according to standard methods, screened using lytA qPCR and serotyped by microarray. Village-level vaccination coverage, for the resident communities of the recruited cases, is determined using administrative data or community survey. Our analysis will investigate the relationship between VT carriage among undervaccinated cases (indirect effects) and vaccine coverage using generalised estimating equations. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the relevant ethics committees at participating sites. The results are intended for publication in open-access peer-reviewed journals and will demonstrate methods suitable for low- and middle-income countries to monitor vaccine impact and inform vaccine policy makers about the PCV coverage required to achieve indirect protection
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